Best Enterprise Data Science and Machine Learning Platforms - Page 2

How Many Data Science and Machine Learning Platforms Products Does G2 Track?

Total Products under this Category: 1,731

Category Stats (Nov 2026)

  • Average Rating: 4.45/5 (↓0.01 vs Oct 2026) The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: Braintrust Data (+1.99%) - Among all products in this category, Braintrust Data recorded the largest rating increase compared to last month

Last updated: November 01, 2026

How Does G2 Rank Data Science and Machine Learning Platforms Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 15,900+ Authentic Reviews
  • 1,731+ Products
  • Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

G2 Grid® for Data Science and Machine Learning Platforms

G2 Grid® for Data Science and Machine Learning Platforms plotting products by satisfaction and market presence

Highlighted products: Databricks, Gemini platform, SAS Viya, Dataiku, Alteryx, IBM watsonx.ai, Deep Learning VM Image, and MATLAB.

Underlying data: [Grid® JSON](https://www.g2.com/categories/data-science-and-machine-learning-platforms/grids.json?focus%5B%5D=databricks&focus%5B%5D=gemini-platform&focus%5B%5D=sas-sas-viya&focus%5B%5D=dataiku&focus%5B%5D=alteryx&focus%5B%5D=ibm-watsonx-ai&focus%5B%5D=deep-learning-vm-image&focus%5B%5D=matlab&segment=enterprise)

Teradata Autonomous Knowledge Platform

Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI. Learn more at Teradata.com.

Average Rating: 4.3/5.0

Total Reviews: 354

How Do G2 Users Rate Teradata Autonomous Knowledge Platform?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.3/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.9/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.0/10 (Category avg: 8.6/10)

Who Is the Company Behind Teradata Autonomous Knowledge Platform?

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 69% Large, 22% Medium

What Do G2 Reviewers Say About Teradata Autonomous Knowledge Platform?

AI-generated summary from verified user reviews

Pros
  • Users praise the high performance of Teradata Autonomous Knowledge Platform, noting its speed and reliability in data analysis.
  • Users benefit from the high speed of Teradata Autonomous Knowledge Platform, enabling fast and efficient data analysis.
  • Users appreciate the high-performance analytics of Teradata's platform, benefiting from fast, scalable data analysis and management.
  • Users value the scalability of Teradata Autonomous Knowledge Platform, enabling efficient handling of complex analytics and workloads.
  • Users appreciate the ability to handle large datasets efficiently, enabling powerful analysis and fast data insights.
Cons
  • Users find the steep learning curve of Teradata Autonomous Knowledge Platform challenging, impacting initial productivity during adoption.
  • Users find the steep learning curve challenging, making advanced features difficult to navigate for non-technical users.
  • Users find the complexity of the Teradata Autonomous Knowledge Platform challenging, especially for non-technical users.
  • Users find Teradata Autonomous Knowledge Platform not user-friendly, particularly for non-technical users navigating its outdated interface.
  • Users criticize the outdated user interface, noting it lacks intuitiveness and is difficult for non-core data team members.

What Are Recent G2 Reviews of Teradata Autonomous Knowledge Platform?

What Are G2 Users Discussing About Teradata Autonomous Knowledge Platform?

Posit Team

Posit is a Public Benefit Corporation building open-source software and an enterprise data science platform. We created the RStudio IDE, Shiny, Positron, and Quarto — tools used by millions of data scientists, machine learning engineers, and researchers worldwide, including teams at 25% of the Fortune Global 100. Our commercial products help organizations put those tools into production: Posit Workbench provides centralized development environments supporting Positron, RStudio, VS Code, and Jupyter; Posit Connect handles publishing and deployment for Shiny, AI applications, Streamlit, Dash, FastAPI, Flask, Bokeh, and more; and Posit Package Manager provides security-compliant package management for R and Python.

Average Rating: 4.5/5.0

Total Reviews: 569

How Do G2 Users Rate Posit Team?

  • Application: 8.4/10 (Category avg: 8.5/10)
  • Managed Service: 8.3/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.3/10 (Category avg: 8.6/10)

Who Is the Company Behind Posit Team?

  • Seller: Posit
  • Year Founded: 2009
  • HQ Location: Boston, US
  • LinkedIn® Page: www.linkedin.com
    439 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Research Assistant, Graduate Research Assistant
  • Top Industries: Higher Education, Information Technology and Services
  • Company Size: 49% Large, 26% Medium

What Do G2 Reviewers Say About Posit Team?

AI-generated summary from verified user reviews

Pros
  • Users commend Posit Team for its ease of use, enabling smooth workflows and efficient data analysis without unnecessary distractions.
  • Users praise the ease of use and integration in Posit, enhancing productivity and focus on data analysis.
  • Users value Posit Team's strong commitment to open source, enhancing their experience with excellent software and community support.
  • Users commend the reliable customer support of Posit Team, making their data science journey seamless and efficient.
  • Users value the easy integrations of Posit Team, enhancing their workflow and simplifying setups with other tools.
Cons
  • Users experience slow performance with large datasets, affecting workflow and necessitating improvements for a smoother usage.
  • Users find the learning curve challenging, especially for beginners trying to grasp advanced features initially.
  • Users often face performance issues with Posit, particularly when handling larger datasets and needing more powerful hardware.
  • Users find the steep learning curve of Posit Team challenging, especially for beginners navigating advanced features.
  • Users experience lagging performance with Posit, particularly with large datasets, impacting productivity and workflow continuity.

What Are Recent G2 Reviews of Posit Team?

What Are G2 Users Discussing About Posit Team?

Google Cloud AutoML

Google Cloud AutoML is a suite of machine learning products designed to enable developers with limited expertise to train high-quality custom models tailored to their specific business needs. By leveraging Google's advanced transfer learning and neural architecture search technologies, AutoML simplifies the process of building, deploying, and scaling machine learning models, making AI more accessible to a broader audience. Key Features and Functionality: - Automated Model Training: AutoML automates the selection of model architecture and hyperparameter tuning, reducing the need for manual intervention and specialized knowledge. - User-Friendly Interface: The platform offers an intuitive graphical interface that allows users to upload data, train models, and manage deployments with ease. - Versatile Model Types: AutoML supports various data types and tasks through specialized services: - AutoML Vision: For image classification and object detection. - AutoML Natural Language: For text classification, sentiment analysis, and entity recognition. - AutoML Translation: For creating custom translation models between language pairs. - AutoML Video Intelligence: For video classification and object tracking. - AutoML Tables: For structured data tasks like regression and classification. - Seamless Integration: AutoML integrates with other Google Cloud services, facilitating efficient data management, model deployment, and scalability. Primary Value and Problem Solving: Google Cloud AutoML democratizes machine learning by enabling users without deep technical expertise to develop and deploy custom models. This accessibility allows businesses to harness the power of AI to solve complex problems, such as improving customer experiences through personalized recommendations, automating content moderation, enhancing language translation services, and gaining insights from large datasets. By reducing the barriers to entry, AutoML empowers organizations to innovate and stay competitive in their respective industries.

Average Rating: 4.3/5.0

Total Reviews: 50

How Do G2 Users Rate Google Cloud AutoML?

  • Natural Language Understanding: 9.4/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.4/10 (Category avg: 8.6/10)

Who Is the Company Behind Google Cloud AutoML?

  • Seller: Google
  • Year Founded: 1998
  • HQ Location: Mountain View, CA
  • LinkedIn® Page: www.linkedin.com
    301,144 employees on LinkedIn®
  • Ownership: NASDAQ:GOOG
  • Phone: +1 (650) 253-0000

Who Uses This Product?

  • Top Industries: Information Technology and Services
  • Company Size: 39% Medium, 39% Small

What Do G2 Reviewers Say About Google Cloud AutoML?

AI-generated summary from verified user reviews

Pros
  • Users value the easy AI integration of Google Cloud AutoML, simplifying the process of developing high-quality models.
  • Users appreciate the ease of use of Google Cloud AutoML, enabling effortless model training without deep expertise.
  • Users appreciate the easy integrations with other Google Cloud services, enhancing their machine learning experience effortlessly.
  • Users appreciate the seamless integration of Google Cloud AutoML with other Google services, enhancing their overall experience.
  • Users find Google Cloud AutoML's intuitive interface essential for easily training high-quality machine learning models.
Cons
  • Users find the pricing expensive for small projects or students, making it less accessible for budget-conscious individuals.
  • Users find the pricing to be expensive, making it challenging for small projects or students to utilize Google Cloud AutoML.

What Are Recent G2 Reviews of Google Cloud AutoML?

What Are G2 Users Discussing About Google Cloud AutoML?

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Intelligence Center X AI Studio

Rapidminer AI Studio is a data science tool that anyone can use to design and prototype highly explainable AI and machine learning models that help build trust throughout an organization. Rapidminer AI Studio includes: - Full generative AI functionality with access to hundreds of large language models (LLMs). - Intuitive and powerful drag-and-drop canvases that give users code-like control without complexity. - Award-winning auto ML with automated clustering, predictive modeling, feature engineering, and time series forecasting. - Data connectivity, exploration, and preparation. - Deploy and manage AI projects and models at enterprise scale. - Collaborate with team members in the same environment without having to worry about overwriting each other's work. - Unify the entire data science lifecycle from data exploration and machine learning to model operations and visualization and deploy in the cloud. Rapidminer AI Studio helps users make powerful insights accessible to the entire organization and can scale seamlessly for users and enterprises. Rapidminer AI studio enables organizations to derive significant value from AI with minimal cost and operational impact.

Average Rating: 4.6/5.0

Total Reviews: 511

How Do G2 Users Rate Intelligence Center X AI Studio?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.2/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.6/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.5/10 (Category avg: 8.6/10)

Who Is the Company Behind Intelligence Center X AI Studio?

Who Uses This Product?

  • Who Uses This: Student, Professor
  • Top Industries: Higher Education, Education Management
  • Company Size: 42% Small, 31% Large

What Do G2 Reviewers Say About Intelligence Center X AI Studio?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the user-friendly interface of Intelligence Center X AI Studio, enabling efficient machine learning without coding.
  • Users value the user-friendly machine learning access of Intelligence Center X AI Studio, simplifying model building and deployment.
  • Users appreciate the seamless AI integration of Intelligence Center X AI Studio, enhancing productivity and simplifying workflows.
  • Users benefit from the advanced machine learning and automation capabilities of Intelligence Center X AI Studio, enhancing decision-making.
  • Users value the automation features of Intelligence Center X AI Studio for enhancing efficiency in data processes.
Cons
  • Users find the complexity of the platform challenging, especially with unclear documentation and lack of multilingual support.
  • Users face slow performance and freezing issues when managing large datasets in Intelligence Center X AI Studio.
  • Users experience slow performance and freezing issues, especially when managing large or complex datasets in Intelligence Center X AI Studio.
  • Users find the product complicated and struggle with the lack of support in Japanese, affecting usability.
  • Users find the complexity of usage in Intelligence Center X AI Studio challenging, especially with limited support in Japanese.

What Are Recent G2 Reviews of Intelligence Center X AI Studio?

What Are G2 Users Discussing About Intelligence Center X AI Studio?

KNIME

KNIME helps everybody make sense of data. Its free and open source KNIME Analytics Platform enables anyone — whether they come from a business, technical or data background — to intuitively work with data, every day. KNIME Business Hub is the commercial complement to KNIME Analytics Platform and enables users to collaborate on data science and share insights across the organization. Together, the products support the complete data science lifecycle, allowing teams at all levels of analytics readiness to support the operationalization of data and to build a scalable data science practice.

Average Rating: 4.5/5.0

Total Reviews: 126

How Do G2 Users Rate KNIME?

  • Application: 8.5/10 (Category avg: 8.5/10)
  • Managed Service: 7.6/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.1/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.2/10 (Category avg: 8.6/10)

Who Is the Company Behind KNIME?

  • Seller: KNIME
  • Company Website:
  • Year Founded: 2008
  • HQ Location: Zurich, Switzerland
  • LinkedIn® Page: www.linkedin.com
    245 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Information Technology and Services, Higher Education
  • Company Size: 43% Large, 32% Medium

What Do G2 Reviewers Say About KNIME?

AI-generated summary from verified user reviews

Pros
  • Users find the ease of use in KNIME invaluable, allowing non-technical individuals to efficiently build workflows.
  • Users love the coding ease of KNIME, making data analysis accessible to both beginners and non-technical users.
  • Users find KNIME to have a user-friendly learning curve, enabling quick access to data solutions without coding skills.
  • Users find KNIME to be a user-friendly learning experience that simplifies complex data analysis without coding.
  • Users appreciate the user-friendly data visualization tools of KNIME, making complex tasks accessible for all skill levels.
Cons
  • Users find the initial learning difficulty in KNIME challenging, especially for those new to data science concepts.
  • Users often face memory availability issues with KNIME, impacting performance and usability, especially with large files.
  • Users often face storage limitations, experiencing memory availability issues and slow performance with large files in KNIME.
  • Users feel that data management issues like file handling and reading from databases hinder their experience with KNIME.
  • Users note the lack of learning resources for KNIME, which hinders their ability to fully utilize the tool.

What Are Recent G2 Reviews of KNIME?

What Are G2 Users Discussing About KNIME?

IBM Decision Optimization

IBM Decision Optimization is a family of prescriptive analytics products that combines mathematical and AI techniques to help with business decision-making including operational, tactical and strategic planning and scheduling use cases. The solutions enable business decision-makers to choose the optimal course of action from millions of alternatives when faced with decisions that involve multiple variables, trade-off possibilities and complex constraints. The solution incorporates powerful optimization solvers namely CPLEX Optimizer and CP Optimizer to solve the breadth of optimization problems including mathematical and constraint programming and constraint-based scheduling models. Learn more about this portfolio here https://www.ibm.com/analytics/decision-optimization IBM ILOG CPLEX Optimization Studio is one of the products within the IBM Decision Optimization portfolio. Organizations across industries are using IBM ILOG CPLEX Optimization Studio to drive operational efficiency and generate significant ROI by optimizing planning, scheduling, pricing and other business decisions. The offering provides users the flexibility to develop optimization models either using general programming language APIs like Python, Java, or using Optimization Programming Language (OPL). The powerful CPLEX optimization engines can deliver the power necessary to solve very large, real- world optimization problems at the speed required for today’s interactive decision optimization applications. Learn more about this product here - https://www.ibm.com/products/ilog-cplex-optimization-studio IBM Decision Optimization is also included within Watson Studio Premium for Cloud Pak for Data to enable data science teams to capitalize on the power of prescriptive analytics and build innovative solutions using a combination of techniques like machine learning and optimization. Data science teams can easily demonstrate business value of optimization by leveraging tools like visual dashboards & modeling assistant to quickly build models, test/evaluate multiple scenarios, solve using powerful optimization engines and deploy the models easily . IBM Decision Optimization solutions bring more than 30 years of experience in the field and is a proven optimization technology and organizations across industries are using IBM Decision Optimization solutions to run their mission-critical decision-making applications and have benefited by way of reduction in operating costs, increase in revenue and accelerated time to value.

Average Rating: 4.5/5.0

Total Reviews: 35

How Do G2 Users Rate IBM Decision Optimization?

  • Application: 8.3/10 (Category avg: 8.5/10)
  • Managed Service: 8.3/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.3/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind IBM Decision Optimization?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM
  • Phone: 1-866-277-7488

Who Uses This Product?

  • Top Industries: Computer Software, Financial Services
  • Company Size: 59% Large, 22% Small

What Are Recent G2 Reviews of IBM Decision Optimization?

What Are G2 Users Discussing About IBM Decision Optimization?

TensorFlow

TensorFlow is an open-source machine learning library developed by the Google Brain Team, designed to facilitate the creation, training, and deployment of machine learning models across various platforms. It provides a comprehensive ecosystem that supports tasks ranging from simple data flow graphs to complex neural networks, enabling developers and researchers to build and deploy machine learning applications efficiently. Key Features and Functionality: - Flexible Architecture: TensorFlow's architecture allows for deployment across multiple platforms, including CPUs, GPUs, and TPUs, and supports various operating systems such as Linux, macOS, Windows, Android, and JavaScript. - Multiple Language Support: While primarily offering a Python API, TensorFlow also provides support for other languages, including C++, Java, and JavaScript, catering to a diverse developer community. - High-Level APIs: TensorFlow includes high-level APIs like Keras, which simplify the process of building and training models, making machine learning more accessible to beginners and efficient for experts. - Eager Execution: This feature allows for immediate evaluation of operations, facilitating intuitive debugging and dynamic graph building. - Distributed Computing: TensorFlow supports distributed training, enabling the scaling of machine learning models across multiple devices and servers without significant code modifications. Primary Value and Solutions Provided: TensorFlow addresses the challenges of developing and deploying machine learning models by offering a unified, scalable, and flexible platform. It streamlines the workflow from model conception to deployment, reducing the complexity associated with machine learning projects. By supporting a wide range of platforms and languages, TensorFlow empowers users to implement machine learning solutions in diverse environments, from research labs to production systems. Its comprehensive suite of tools and libraries accelerates the development process, fosters innovation, and enables the creation of sophisticated models that can tackle real-world problems effectively.

Average Rating: 4.5/5.0

Total Reviews: 133

How Do G2 Users Rate TensorFlow?

  • Application: 8.7/10 (Category avg: 8.5/10)
  • Managed Service: 8.5/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.7/10 (Category avg: 8.3/10)
  • Ease of Admin: 7.9/10 (Category avg: 8.6/10)

Who Is the Company Behind TensorFlow?

  • Seller: TensorFlow
  • Year Founded: 2016
  • HQ Location: Centre Urbain Nord, TN
  • LinkedIn® Page: www.linkedin.com
    1 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer, Senior Software Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 52% Small, 26% Medium

What Do G2 Reviewers Say About TensorFlow?

AI-generated summary from verified user reviews

Pros
  • Users find TensorFlow to have a user-friendly interface and excellent support for creating and deploying ML models.
  • Users value the efficient AI integration of TensorFlow, enhancing their machine learning projects with powerful features.
  • Users appreciate the ease of use of TensorFlow, making it accessible for newcomers to machine learning.
  • Users value the model variety in TensorFlow, enhancing integration for web and mobile development.
  • Users commend TensorFlow for its scalability, enabling effective management of both small and large-scale machine learning projects.
Cons
  • Users find the steep learning curve of TensorFlow challenging, particularly beginners struggling with documentation and debugging.
  • Users note the complexity of TensorFlow, particularly on Windows, which hampers usability and performance for many applications.
  • Users find the difficult learning curve in TensorFlow challenging, especially for beginners navigating complex concepts and APIs.
  • Users struggle with complicated error handling, making debugging difficult and creating a steep learning curve for beginners.
  • Users notice slow performance in TensorFlow, particularly with complex models and during smaller projects.

What Are Recent G2 Reviews of TensorFlow?

What Are G2 Users Discussing About TensorFlow?

SAP Business Data Cloud

SAP Business Data Cloud is a fully managed software-as-a-service (SaaS) solution that unifies and governs SAP data and connects with third-party data. As an evolution of the company's data, planning, and analytics solutions, SAP Business Data Cloud brings together SAP Datasphere, SAP Analytics Cloud, and SAP Business Warehouse with a unified experience that delivers insights across all lines of business. In addition, SAP Databricks is natively available in Business Data Cloud - bringing the power of Databricks Data Intelligence Platform capabilities to the product. SAP Business Data Cloud connects data by leveraging business data fabric principles, making it easier to discover, share, govern, and model this data. It includes SAP Databricks as a first-party data service. The platform combines prebuilt applications and data products across all lines of business. It provides fully managed, curated data products across all lines of business and eliminate the costs of data extracts. Users can build on SAP’s curated data products with their domain expertise, and deliver Intelligent Applications through the Business Data Cloud ecosystem. These intelligent applications are adaptive, AI-powered applications that learn from your data, understand business context, and act on your behalf to transform business outcomes.

Average Rating: 4.2/5.0

Total Reviews: 97

How Do G2 Users Rate SAP Business Data Cloud?

  • Ease of Admin: 7.5/10 (Category avg: 8.6/10)

Who Is the Company Behind SAP Business Data Cloud?

  • Seller: SAP
  • Company Website:
  • Year Founded: 1972
  • HQ Location: Walldorf
  • LinkedIn® Page: www.linkedin.com
    149,349 employees on LinkedIn®
  • Ownership: NYSE:SAP

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 43% Large, 28% Small

What Do G2 Reviewers Say About SAP Business Data Cloud?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use of SAP Business Data Cloud, enhancing seamless data access and integration across systems.
  • Users appreciate the robust functionality of SAP Business Data Cloud for seamless data governance and integration across various sources.
  • Users appreciate the seamless integration capabilities of SAP Business Data Cloud, enhancing data governance and analytics efficiency.
  • Users appreciate the seamless data discovery capabilities of SAP Business Data Cloud, enhancing trust and efficiency across the organization.
  • Users value the seamless integration of SAP Business Data Cloud, which simplifies access to reliable data across systems.
Cons
  • Users find the complexity of setup and learning curve challenging, requiring significant effort and training to navigate.
  • Users face a difficult learning curve with SAP Business Data Cloud, complicating the adoption process and integration efforts.
  • Users often face integration issues with non-SAP systems, requiring extra effort for seamless configuration and management.
  • Users note that the cost considerations for SAP Business Data Cloud can be a significant barrier for smaller teams.
  • Users struggle with the learning curve of SAP Business Data Cloud, finding it complex and challenging for new users.

What Are Recent G2 Reviews of SAP Business Data Cloud?

Domo

Domo’s AI and data platform business is now part of Progress Software. Domo's cloud-native AI data readiness platform complements and significantly broadens Progress' data platform offerings, creating powerful synergies to deliver innovative, secure and scalable AI data readiness solutions worldwide. Together, these capabilities will help customers turn fragmented enterprise data and knowledge into governed, AI-ready intelligence, improving the security, governance and cost of AI-powered initiatives. Domo is the agentic platform for the intelligent enterprise, helping organizations connect, govern, activate, and distribute data and AI across their business. Built for enterprises, Domo works with existing cloud data platforms such as Snowflake, BigQuery, and Databricks to help teams turn governed data into AI-powered agents, apps, workflows, and analytics. Domo is built on three layers. The data foundation connects and governs data across cloud data platforms and business systems. The activation layer enables organizations to build AI agents, apps, workflows, automations, and dashboards on top of that foundation. The distribution layer delivers intelligence where work happens through embedded apps, mobile, dashboards, and AI assistants using Model Context Protocol (MCP). Governance underpins every layer, helping organizations scale AI and data products with security and trust. Key capabilities include: • Connecting and governing data across cloud data platforms and enterprise applications. • Building AI agents, apps, workflows, automations, dashboards, and analytics. • Delivering data and AI through dashboards, embedded apps, AI assistants, and AI agents. • Supporting both low-code and pro-code development for business and technical teams. • Applying governance, security, and access controls across data and AI. Organizations use Domo for AI agents, apps, and workflows, as well as business intelligence, operational analytics, embedded analytics, and executive reporting. By combining governed data, AI activation, app development, and distribution in a single platform, Domo helps organizations build and scale trusted data products across the enterprise.

Average Rating: 4.3/5.0

Total Reviews: 1,078

How Do G2 Users Rate Domo?

  • Application: 5.9/10 (Category avg: 8.5/10)
  • Managed Service: 6.4/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 5.8/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.1/10 (Category avg: 8.6/10)

Who Is the Company Behind Domo?

  • Seller: Domo
  • Company Website:
  • Year Founded: 2010
  • HQ Location: American Fork, UT
  • LinkedIn® Page: www.linkedin.com
    1,288 employees on LinkedIn®
  • Ownership: NASDAQ: DOMO

Who Uses This Product?

  • Who Uses This: Data Analyst, Business Analyst
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 50% Medium, 28% Large

What Do G2 Reviewers Say About Domo?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use of Domo, appreciating its intuitive interface and straightforward data integration capabilities.
  • Users love Domo for its intuitive data visualization, making it easy to create dashboards and extract insights efficiently.
  • Users find Domo extremely intuitive, enabling quick dashboard creation and seamless integration of diverse data sources.
  • Users value the easy integrations of Domo, allowing seamless connection to numerous data sources for insightful analytics.
  • Users praise Domo's seamless integrations, enabling easy connections to various data sources for effective analytics and monitoring.
Cons
  • Users find the steep learning curve of Domo challenging, impacting onboarding and productivity for some staff.
  • Users find it challenging to keep up with missing features and updates, necessitating dedicated resources for tracking.
  • Users face significant data management issues, finding it challenging to secure, clean, and efficiently manage datasets in Domo.
  • Users find Domo's pricing to be expensive and confusing, especially as usage and storage requirements increase.
  • Users find Domo's complexity challenging, citing issues in data management and a lack of support for troubleshooting.

What Are Recent G2 Reviews of Domo?

What Are G2 Users Discussing About Domo?

Red Hat OpenShift Data Science

Red Hat® OpenShift® AI is a flexible, scalable artificial intelligence (AI) and machine learning (ML) platform that enables enterprises to create and deliver AI-enabled applications at scale across hybrid cloud environments. Built using open source technologies, OpenShift AI provides trusted, operationally consistent capabilities for teams to experiment, serve models, and deliver innovative apps.

Average Rating: 4.4/5.0

Total Reviews: 42

How Do G2 Users Rate Red Hat OpenShift Data Science?

  • Application: 8.7/10 (Category avg: 8.5/10)
  • Managed Service: 8.8/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.7/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.2/10 (Category avg: 8.6/10)

Who Is the Company Behind Red Hat OpenShift Data Science?

  • Seller: Red Hat
  • Year Founded: 1993
  • HQ Location: Raleigh, NC
  • LinkedIn® Page: www.linkedin.com
    19,487 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Market Research, Computer Software
  • Company Size: 40% Large, 38% Medium

What Are Recent G2 Reviews of Red Hat OpenShift Data Science?

What Are G2 Users Discussing About Red Hat OpenShift Data Science?

IBM SPSS Modeler

The IBM SPSS Modeler is a leading, visual data science and machine learning solution. It helps enterprises accelerate time to value and desired outcome by speeding the operational tasks for data scientists. Leading organizations worldwide rely on IBM for data discovery, predictive analytics, model management and deployment, and machine learning to monetize data assets. The IBM SPSS Modeler empowers organizations to tap data assets and modern applications with complete, out-of-box algorithms and models, suited for hybrid, multi-cloud environments with robust governance and security posture. • Take advantage of open source based innovation including R or Python • Empower data scientists of all skills – programmatic and visual • Exploit multi-cloud approach - on-prem, public or private clouds • Start small and scale to enterprise-wide, governed approach

Average Rating: 4.0/5.0

Total Reviews: 128

How Do G2 Users Rate IBM SPSS Modeler?

  • Application: 7.5/10 (Category avg: 8.5/10)
  • Managed Service: 7.6/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 6.4/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.1/10 (Category avg: 8.6/10)

Who Is the Company Behind IBM SPSS Modeler?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM
  • Phone: 1-866-277-7488

Who Uses This Product?

  • Top Industries: Higher Education, Education Management
  • Company Size: 53% Large, 24% Medium

What Do G2 Reviewers Say About IBM SPSS Modeler?

AI-generated summary from verified user reviews

Pros
  • Users value the robust analytical modeling capabilities of IBM SPSS Modeler, enhancing their data manipulation and preparation tasks.
  • Users appreciate the seamless data connection in IBM SPSS Modeler, enhancing efficiency in data manipulation and analysis.
  • Users value the direct data connection in IBM SPSS Modeler, enabling seamless data manipulation and integration.
  • Users value the seamless data connection and manipulation features of IBM SPSS Modeler for enhanced analytics.
  • Users value the data visualization capabilities of IBM SPSS Modeler, enhancing seamless data manipulation and analysis.
Cons
  • Users believe the licensing fees are too expensive, making the cost per user quite high.
  • Users are concerned about the expensive licensing, noting that costs can be prohibitive for multiple users.

What Are Recent G2 Reviews of IBM SPSS Modeler?

What Are G2 Users Discussing About IBM SPSS Modeler?

Anaconda Core

Anaconda is built to advance AI with open source at scale, giving builders and organizations the confidence to increase productivity, and save time, spend and risk associated with open source. 95% of the Fortune 500 including Panasonic, AmTrust, Booz Allen Hamilton and over 50 million users rely on the value The Anaconda Platform delivers through a centralized approach to sourcing, securing, building, and deploying AI. With 21 billion downloads and growing, Anaconda has established itself as the gold standard for Python, data science, and AI and the enterprise-ready solution of choice for AI innovation. Anaconda is available across hybrid AI environments and cloud platforms such as AWS, Microsoft Azure, Databricks, Snowflake and more with backing from world-class investors including Insight Partners. Learn more at https://www.anaconda.com.

Average Rating: 4.5/5.0

Total Reviews: 234

How Do G2 Users Rate Anaconda Core?

  • Application: 8.9/10 (Category avg: 8.5/10)
  • Managed Service: 8.6/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 8.5/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind Anaconda Core?

Who Uses This Product?

  • Who Uses This: Student, Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 38% Small, 25% Large

What Do G2 Reviewers Say About Anaconda Core?

AI-generated summary from verified user reviews

Pros
  • Users find the ease of use of Anaconda Core exceptional, simplifying data science workflows for beginners and experts alike.
  • Users find Anaconda Core's setup ease invaluable, simplifying environment management and enhancing focus on data analysis tasks.
  • Users commend Anaconda Core for its efficiency in dependency management, simplifying environment setup and enhancing productivity.
  • Users appreciate the intuitive interface of Anaconda Core, enhancing their learning experience in data analysis and machine learning.
  • Users love the coding ease of Anaconda Core, facilitating quick setup and seamless project management in data science.
Cons
  • Users face data management issues with Anaconda due to outdated packages and its large installation size affecting performance.
  • Users often experience slow performance, especially with resource-heavy installations and sluggish dependency resolution in Anaconda Core.
  • Users find Anaconda Core lacking features due to overwhelming package installations and poor feature descriptions.
  • Users feel that the limited features of Anaconda Core hinder usability and access to the latest updates.
  • Users are concerned about the limited storage requirements of Anaconda Core, which can strain available disk space.

What Are Recent G2 Reviews of Anaconda Core?

What Are G2 Users Discussing About Anaconda Core?

Deepnote

Deepnote is a data workspace where agents and humans work together. It's designed to simplify data exploration, accelerate analysis, and quickly deliver actionable insights for you and your team. Unlike outdated tools such as Jupyter, Deepnote is built with the next decade in mind. Deepnote gives anyone working with data superpowers. It unifies your data workflow through an integrated semantic layer, preparing your data for advanced AI applications. You can also leverage our AI data copilot to chat with your data, create charts, write code, or turn your AI notebooks into fully-fledged data dashboards or apps. Combine data, SQL or Python code, and visualizations side-by-side on a flexible canvas - enhanced with cutting-edge AI reasoning models. 🤖 Analyze with AI • Generate code and visualizations by describing your goal. • Auto-write, run, and debug code with AI. • Move faster with context-aware AI suggestions. 🔗 Unify • Connect to 60+ data sources like BigQuery, Snowflake, and PostgreSQL. • Combine Python and SQL in one notebook. • Build reusable ETL, analytics, and metric modules. • Create a semantic layer with shared definitions and trusted metrics. ⚖️ Scale • Instantly boost compute power, more included than Colab. • Schedule jobs and get notified with fresh results. • Organize work in projects and folders for team clarity. • Manage workflows via REST API. 🚀 Launch • Turn notebooks into dashboards or data apps, natively or with Streamlit. • Let users explore data with interactive inputs. • Share secure, live apps in one click.

Average Rating: 4.5/5.0

Total Reviews: 384

How Do G2 Users Rate Deepnote?

  • Application: 8.0/10 (Category avg: 8.5/10)
  • Managed Service: 7.9/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 7.2/10 (Category avg: 8.3/10)
  • Ease of Admin: 8.7/10 (Category avg: 8.6/10)

Who Is the Company Behind Deepnote?

  • Seller: Deepnote
  • Company Website:
  • Year Founded: 2019
  • HQ Location: San Francisco , US
  • LinkedIn® Page: www.linkedin.com
    21 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Student, Data Analyst
  • Top Industries: Computer Software, Higher Education
  • Company Size: 67% Small, 25% Medium

What Do G2 Reviewers Say About Deepnote?

AI-generated summary from verified user reviews

Pros
  • Users find Deepnote's ease of use invaluable for collaborative data science, enhancing productivity and streamlining workflows.
  • Users value the real-time collaboration features of Deepnote, enhancing teamwork and streamlining workflows effortlessly.
  • Users appreciate the easy integrations in Deepnote, enhancing collaboration and streamlining access to data sources and analysis.
  • Users value the real-time collaboration in Deepnote, enhancing teamwork and streamlining the workflow effectively.
  • Users value the seamless data management in Deepnote, enhancing collaboration and analysis through intuitive integrations and features.
Cons
  • Users experience slow performance in Deepnote, especially with larger notebooks and when running queries or reports.
  • Users feel that Deepnote has limited features which hinder its full potential for AI app integration and usability.
  • Users experience data management issues in Deepnote, particularly with context maintenance and cluttered cell generation during AI interactions.
  • Users find the missing features in Deepnote limiting, particularly for AI app development and data visualization improvements.
  • Users find Deepnote lacking features for integration and usability, hindering their overall data analysis experience.

What Are Recent G2 Reviews of Deepnote?

What Are G2 Users Discussing About Deepnote?

Hex

Hex is the world’s favorite AI Analytics platform. With Hex, anyone can explore data using natural language, with or without code, all on trusted context, in one AI-powered platform. Get started now > https://app.hex.tech/signup?source=g2 Get a demo > https://hex.tech/request-a-demo/?source=g2

Average Rating: 4.5/5.0

Total Reviews: 432

How Do G2 Users Rate Hex?

  • Application: 6.9/10 (Category avg: 8.5/10)
  • Managed Service: 6.8/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 5.1/10 (Category avg: 8.3/10)
  • Ease of Admin: 9.0/10 (Category avg: 8.6/10)

Who Is the Company Behind Hex?

  • Seller: Hex Tech
  • Company Website:
  • Year Founded: 2019
  • HQ Location: San Francisco, US
  • LinkedIn® Page: www.linkedin.com
    280 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Analyst, Data Scientist
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 53% Medium, 22% Small

What Do G2 Reviewers Say About Hex?

AI-generated summary from verified user reviews

Pros
  • Users commend Hex for its ease of use, enabling effortless data analysis without needing extensive technical skills.
  • Users appreciate the ease of use with SQL queries in Hex, enhancing efficiency and data exploration for all team members.
  • Users appreciate the ease of use and efficient data manipulation in Hex, enhancing their data management experience.
  • Users value the efficient SQL querying in Hex, enhancing team collaboration and simplifying data exploration with AI features.
  • Users praise Hex for its effortless data analysis, enabling self-service insights with powerful AI tools and user-friendly features.
Cons
  • Users find Hex's limited features frustrating, noting a lack of options and poor usability affecting overall experience.
  • Users find Hex lacking in essential features like multiple modes and basic coding shortcuts, affecting usability.
  • Users find Hex lacking features, particularly in missing shortcuts and having confusing modes and permissions.
  • Users note the limited visualization options in Hex, hindering their ability to create effective dashboards and graphics.
  • Users express concerns about data management issues, including inaccuracies and organization challenges in Hex's workbooks.

What Are Recent G2 Reviews of Hex?

What Are G2 Users Discussing About Hex?

IBM Cloud Pak for Data

IBM Cloud Pak® for Data is a fully integrated data and AI platform that modernizes how businesses collect, organize and analyze data, forming the foundation to infuse AI across their organization. Running on Red Hat OpenShift and available on any cloud, this unified platform helps companies automate the end-to-end AI lifecycle. The intelligent data fabric in IBM Cloud Pak for Data enables automated distributed queries at scale without data movement; automated discovery and understanding of business-ready data; automated universal privacy and usage policies across the data ecosystem; and optimized model training, accuracy and explainability. View the demo: https://mediacenter.ibm.com/media/1_je41fqqz. The platform delivers on the below use cases: • Data access and availability – Eliminate data silos and simplify your data landscape to enable faster, cost-effective extraction of value from your data. • Data quality and governance - Apply governance solutions and methodologies to deliver trusted, business data. • Data privacy and security - Fully understand and manage sensitive data with a pervasive privacy framework. • ModelOps - Automate the AI lifecycle and synchronize application and model pipelines to scale AI deployments. • AI governance – Ensure your AI is transparent, compliant and trustworthy with greater visibility into model development, with capabilities such as explainable AI, model risk management and bias detection. • AI for Financial Operations - Automate and integrate planning across your organization, from financial planning & analysis to workforce planning, sales forecasting and supply chain planning. • AI for Customer care - Reduce time to resolution, decrease call volume and increase customer satisfaction. IBM Watson Assistant (WA) can provide AI-powered automated assistance and enable human agents to better handle inquiries. IBM Watson Discovery (WD) complements Watson Assistant and can help unlock insights from complex business content. Discover IBM Cloud Pak for Data Industry Accelerators: https://dataplatform.cloud.ibm.com/gallery?context=cpdaas See a case study: https://mediacenter.ibm.com/media/1_sr6lx8sz Try at no-cost: http://ibm.biz/dataplatformtrial

Average Rating: 4.3/5.0

Total Reviews: 71

How Do G2 Users Rate IBM Cloud Pak for Data?

  • Application: 8.8/10 (Category avg: 8.5/10)
  • Managed Service: 8.5/10 (Category avg: 8.3/10)
  • Natural Language Understanding: 9.2/10 (Category avg: 8.3/10)
  • Ease of Admin: 7.6/10 (Category avg: 8.6/10)

Who Is the Company Behind IBM Cloud Pak for Data?

  • Seller: IBM
  • Year Founded: 1911
  • HQ Location: Armonk, New York, United States
  • LinkedIn® Page: www.linkedin.com
    344,328 employees on LinkedIn®
  • Ownership: SWX:IBM
  • Phone: 1-866-277-7488

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 52% Large, 27% Small

What Are Recent G2 Reviews of IBM Cloud Pak for Data?

Bijou Barry
BB
Researched and written by Bijou Barry
Updated